GUJARATI HANDWRITTEN NUMERAL OPTICAL CHARACTER THROUGH NEURAL NETWORK AND SKELETONIZATION
Abstract: This paper
deals with an
optical character recognition (OCR)
system for handwritten
Gujarati numbers. One may
find so much
of work for
Indian languages like Hindi, Kannada, Tamil, Bangala,
Malayalam, Gurumukhi etc, but
Gujarati is a
language for which
hardly any work
is traceable especially for handwritten characters. The features of Gujarati digits
are abstracted by
four different profiles
of digits. Skeletonization and
binarization are also
done for preprocessing of
handwritten numerals before
their classification. This work has achieved approximately 80,5% of success
rate for Gujarati handwritten digit identification.
Index Terms: Optical character
recognition, neural network, feature extraction, Gujarati handwritten digits, skeletonization,
classification
Author: Kamal MORO, Mohammed
FAKIR, Badr Dine EL KESSAB, Belaid BOUIKHALENE, Cherki DAOUI
Journal Code: jptkomputergg130002
